@unpublished {CxExplicada2019,
	title = {Complejidad Explicada},
	year = {2019},
	note = {Traducci{\'o}n de {\textquoteleft}{\textquoteleft}Complexity Explained{\textquoteright}{\textquoteright}},
	url = {https://complexityexplained.github.io},
	author = {Valerie C. Valerio Holgu{\'\i}n and Carlos Gershenson and Jos{\'e} Luis Herrera and Johann H. Mart{\'\i}nez and Manuel Rueda Santos and Oliver L{\'o}pez Corona and Guillermo de Anda J{\'a}uregui and Gerardo I{\~n}iguez and Alfredo J. Morales Guzm{\'a}n and Jos{\'e} R. Nicol{\'a}s Carlock}
}
@unpublished {ComplexityExplained,
	title = {Complexity Explained: A Grassroot Collaborative Initiative to Create a Set of Essential Concepts of Complex Systems.},
	year = {2019},
	note = {https://complexityexplained.github.io},
	abstract = {Complexity science, also called complex systems science, studies how a large collection of components {\textendash} locally interacting with each other at small scales {\textendash} can spontaneously self-organize to exhibit non-trivial global structures and behaviors at larger scales, often without external intervention, central authorities or leaders. The properties of the collection may not be understood or predicted from the full knowledge of its constituents alone. Such a collection is called a complex system and it requires new mathematical frameworks and scientific methodologies for its investigation.},
	doi = {10.17605/OSF.IO/TQGNW},
	url = {https://complexityexplained.github.io},
	author = {Manlio De Domenico and Chico Camargo and Carlos Gershenson and Daniel Goldsmith and Sabine Jeschonnek and Lorren Kay and Stefano Nichele and Jos{\'e} Nicol{\'a}s and Thomas Schmickl and Massimo Stella and Josh Brandoff and {\'A}ngel Jos{\'e} Mart{\'\i}nez Salinas and Hiroki Sayama}
}
@proceedings {211,
	title = {El S{\'\i}ndrome de los Datos Ricos e Informaci{\'o}n Pobre en Deportes de Competici{\'o}n: Perspectiva desde las Ciencias Computacionales y Ciencia de Datos},
	year = {2019},
	address = {Pachuca, M{\'e}xico},
	abstract = {La gran capacidad existente de capturar datos, conlleva la subsecuente responsabilidad de producir informaci{\'o}n confiable, verificable y auditable para la toma de decisiones. En el futbol, la existencia de compa{\~n}{\'\i}as y plataformas con capacidad de medir un sinn{\'u}mero de variables de desempe{\~n}o, ha generado una explosi{\'o}n de datos de dif{\'\i}cil interpretaci{\'o}n. En este sentido, las dificultades relativas al an{\'a}lisis y visualizaci{\'o}n de estos datos, ha derivado en el {\textquotedblleft}S{\'\i}ndrome de los datos ricos e informaci{\'o}n pobre{\textquotedblright}. En este contexto, esta pl{\'a}tica se centra en evaluar las lecciones aprendidas y las perspectivas futuras en el manejo de datos en el futbol, desde una perspectiva computacional y de ciencia de datos. Nuestro enfoque metodol{\'o}gico, parte de la evaluaci{\'o}n de los formatos en que se produce los datos y los tipos de reportes generados para distintos tipos de usuarios. Planteamos una forma adecuada de manejar e interpretar m{\'u}ltiples variables con soporte en t{\'e}cnicas de aprendizaje autom{\'a}tico, con t{\'e}cnicas de ordenaci{\'o}n y clasificaci{\'o}n para discriminar los factores y variables que tienen mayor contribuci{\'o}n en el juego. Finalmente, brindamos informaci{\'o}n sobre perspectivas novedosas para el modelado de los eventos espacio-temporales, que tienen lugar en los partidos, como la aplicaci{\'o}n desde la ciencia de redes, redes de latencia y modelos de gravitaci{\'o}n para el modelado. Nuestra perspectiva computacional y de ciencia de datos brinda la posibilidad de mejores visualizaciones, con el prop{\'o}sito de simplificar el gran n{\'u}mero de dimensiones y categor{\'\i}as que se inspeccionan en el futbol. De esta forma, nos enfocamos en las interacciones relevantes del juego, que dar{\'\i}an soporte a una mejor toma de decisiones por parte de distintos tipos de usuarios, como jugadores, entrenadores y directivos.},
	author = {Nelson Fern{\'a}ndez and Mart{\'\i}n Zumaya and Carlos Gershenson}
}
@unpublished {SAT2019,
	title = {Evasi{\'o}n en IVA: An{\'a}lisis de redes},
	year = {2019},
	note = {Estudio contratado por el SAT},
	url = {http://omawww.sat.gob.mx/gobmxtransparencia/Paginas/documentos/estudio_opiniones/Evasion_en_IVA_Analisis_de_Redes.pdf},
	author = {Carlos Gershenson and Gerardo I{\~n}iguez and Carlos Pineda and Rita Guerrero and Eduardo Islas and Omar Pineda and Mart{\'\i}n Zumaya}
}
@article {Cocho2019,
	title = {Rank-frequency distribution of natural languages: A difference of probabilities approach},
	journal = {Physica A: Statistical Mechanics and its Applications},
	volume = {532},
	year = {2019},
	pages = {121795},
	abstract = {In this paper we investigate the time variation of the rank k of words for six Indo-European languages using the Google Books N-gram Dataset. Based on numerical evidence, we regard k as a random variable whose dynamics may be described by a Fokker{\textendash}Planck equation which we solve analytically. For low ranks the distinct languages behave differently, maybe due to the syntax rules, whereas for k>50 the law of large numbers predominates. We analyze the frequency distribution of words using the data and their adjustment in terms of time-dependent probability density distributions. We find small differences between the data and the fits due to conflicting dynamic mechanisms, but the data show a consistent behavior with our general approach. For the lower ranks the behavior of the data changes among languages presumably, again, due to distinct dynamic mechanisms. We discuss a possible origin of these differences and assess the novel features and limitations of our work.},
	keywords = {Fokker{\textendash}Planck equation, Languages, Master equation, Rank dynamics},
	issn = {0378-4371},
	doi = {10.1016/j.physa.2019.121795},
	url = {https://doi.org/10.1016/j.physa.2019.121795},
	author = {Germinal Cocho and Rosal{\'\i}o F. Rodr{\'\i}guez and Sergio S{\'a}nchez and Jorge Flores and Carlos Pineda and Carlos Gershenson}
}
@proceedings {212,
	title = {Sistemas con Din{\'a}mica Acoplada y Redes de Defensa y Ataque: Representaci{\'o}n de las Interacciones en Juegos de Competici{\'o}n},
	year = {2019},
	address = {Pachuca, M{\'e}xico},
	author = {Nelson Fern{\'a}ndez and V{\'\i}ctor Rivera and Carlos Gershenson}
}
@conference {184,
	title = {Coupled Dynamical Systems and Defense-Attack Networks: Representation of Soccer Players Interactions},
	booktitle = {Conference on Complex Systems},
	year = {2018},
	address = {Thessaloniki, Greece},
	author = {Nelson Fern{\'a}ndez and V{\'\i}ctor Rivera and Yesid Madrid and Guillermo Restrepo and Wilmer Leal and Carlos Gershenson}
}
@unpublished {Gershenson2018,
	title = {Information in Science and Buddhist Philosophy: Towards a Non-Materialistic Worldview},
	year = {2018},
	note = {Preprints 2018120042},
	month = {November},
	abstract = {Information theory has been developed for seventy years with technological applications that have transformed our societies. The increasing ability to store, transmit, and process information is having a revolutionary impact in most disciplines. The goal of this work is to compare the formal approach to information with Buddhist philosophy. Considering both approaches as compatible and complementary, I argue that information theory can improve our understanding of Buddhist philosophy and vice versa. The resulting synthesis leads to a worldview based on information that overcomes limitations of the currently dominating physics-based worldview.},
	doi = {10.20944/preprints201812.0042.v1},
	author = {Carlos Gershenson}
}
@conference {183,
	title = {Modeling Systems with Coupled Dynamics (SCDs): A Multi-Agent, Networks, and Game Theory-based Approach},
	booktitle = {Conference on Complex Systems},
	year = {2018},
	address = {Thessaloniki, Greece},
	author = {Nelson Fern{\'a}ndez and Osman Ortega and Yesid Madrid and Guillermo Restrepo and Wilmer Leal and Carlos Gershenson}
}
@article {Karbovskii2016,
	title = {Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics},
	journal = {Future Generation Computer Systems},
	volume = {79},
	number = {1},
	year = {2018},
	month = {February},
	pages = {155{\textendash}165},
	abstract = {Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents{\textendash}-abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose {PULSE} simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.},
	issn = {0167-739X},
	doi = {10.1016/j.future.2016.10.002},
	url = {http://dx.doi.org/10.1016/j.future.2016.10.002},
	author = {Vladislav Karbovskii and Daniil Voloshin and Andrey Karsakov and Alexey Bezgodov and Carlos Gershenson}
}
@book {ICCS2018,
	title = {Unifying Themes in Complex Systems IX: Proceedings of the Ninth International Conference on Complex Systems},
	series = {Springer Proceedings in Complexity},
	year = {2018},
	publisher = {Springer},
	organization = {Springer},
	address = {Cambridge, MA, USA},
	url = {https://link.springer.com/book/10.1007/978-3-319-96661-8},
	editor = {Alfredo J. Morales and Carlos Gershenson and Dan Braha and Ali A. Minai and Yaneer Bar-Yam}
}
@book {164,
	title = {Conference on Complex Systems 2017 Abstract Booklet},
	year = {2017},
	address = {Cancun, Mexico},
	url = {http://ccs17.unam.mx/booklet.pdf},
	author = {Carlos Gershenson and Jose Luis Mateos}
}
@article {Kolokoltsev2017,
	title = {Improving {\textquoteleft}{\textquoteleft}tail{\textquoteright}{\textquoteright} computations in a BOINC-based Desktop Grid},
	journal = {Open Engineering},
	volume = {7},
	number = {1},
	year = {2017},
	month = {December},
	pages = {371-378},
	doi = {doi:10.1515/eng-2017-0044},
	author = {Kolokoltsev, Yevgeniy and Evgeny Ivashko and Carlos Gershenson}
}
@unpublished {AdaptiveCities,
	title = {Adaptive Cities: A Cybernetic Perspective on Urban Systems},
	year = {2016},
	note = {arXiv preprint 1609.02000},
	url = {https://arxiv.org/abs/1609.02000},
	author = {Carlos Gershenson and Paolo Santi and Carlo Ratti}
}
@inbook {Madrid2016,
	title = {Complexity and Structural Properties in Scale-free Networks},
	booktitle = {Proceedings of the Artificial Life Conference 2016},
	year = {2016},
	pages = {730{\textendash}731},
	abstract = {We apply formal information measures of emergence, self-organization and complexity to scale-free random networks, to explore their association with structural indicators of network topology. Results show that the cumulative number of nodes and edges coincides with an increment of the self-organization and relative complexity, and a loss of the emergence and complexity. Our approach shows a complementary way of studying networks in terms of information.},
	author = {Yesid Madrid and Carlos Gershenson and Nelson Fern{\'a}ndez}
}
@article {Pina-Garcia2016,
	title = {Exploring Dynamic Environments Using Stochastic Search Strategies},
	journal = {Research in Computing Science},
	volume = {121},
	year = {2016},
	pages = {43{\textendash}57},
	url = {http://rcs.cic.ipn.mx/2016_121/Exploring\%20Dynamic\%20Environments\%20Using\%20Stochastic\%20Search\%20Strategies.pdf},
	author = {C. A. Pi{\~n}a-Garc{\'\i}a and Dongbing Gu and Carlos Gershenson and J. Mario Siqueiros-Garc{\'\i}a and E. Robles-Belmont}
}
@inbook {Gershenson2016,
	title = {Improving Urban Mobility by Understanding Its Complexity},
	booktitle = {The Pursuit of Legible Policy: Encouraging Agency and Participation in the Complex Systems of the Contemporary Megalopolis},
	year = {2016},
	pages = {149{\textendash}151},
	publisher = {{Bur{\'o}{\textendash}Bur{\'o}},
	organization = {{Bur{\'o}{\textendash}Bur{\'o}},
	address = {Mexico City, Mexico},
	author = {Carlos Gershenson}
}
@inbook {ALifeXVIntro,
	title = {Introduction},
	booktitle = {Proceedings of the Artificial Life Conference 2016},
	year = {2016},
	pages = {3{\textendash}9},
	author = {Tom Froese and J. Mario Siqueiros and Wendy Aguilar and Eduardo J. Izquierdo and Hiroki Sayama and Carlos Gershenson}
}
@article {Karbovskii2016,
	title = {Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics},
	journal = {Future Generation Computer Systems},
	year = {2016},
	pages = {-},
	abstract = {Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents{\textendash}-abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose \{PULSE\} simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.},
	keywords = {Urgent computing},
	issn = {0167-739X},
	doi = {10.1016/j.future.2016.10.002},
	url = {http://dx.doi.org/10.1016/j.future.2016.10.002},
	author = {Vladislav Karbovskii and Daniil Voloshin and Andrey Karsakov and Alexey Bezgodov and Carlos Gershenson}
}
@inbook {Zapotecatl2016,
	title = {Performance Metrics of Collective Coordinated Motion in Flocks},
	booktitle = {Proceedings of the Artificial Life Conference 2016},
	year = {2016},
	pages = {322{\textendash}329},
	author = {Jorge L. Zapotecatl and Ang{\'e}lica Mu{\~n}oz-Mel{\'e}ndez and Carlos Gershenson}
}
@book {ALifeXV,
	title = {Proceedings of the Artificial Life Conference 2016},
	series = {Complex Adaptive Systems},
	year = {2016},
	month = {July},
	publisher = {MIT Press},
	organization = {MIT Press},
	address = {Cambridge, MA, USA},
	abstract = {The ALife conferences are the major meeting of the artificial life research community since 1987. For its 15th edition in 2016, it was held in Latin America for the first time, in the Mayan Riviera, Mexico, from July 4 -8. The special them of the conference: How can the synthetic study of living systems contribute to societies: scientifically, technically, and culturally? The goal of the conference theme is to better understand societies with the purpose of using this understanding for a more efficient management and development of social systems.},
	isbn = {9780262339360},
	url = {https://mitpress.mit.edu/books/proceedings-artificial-life-conference-2016},
	editor = {Carlos Gershenson and Tom Froese and Jesus M. Siqueiros and Wendy Aguilar and Eduardo J. Izquierdo and Hiroki Sayama}
}
@inbook {Viragh2016,
	title = {Self-organized UAV Traffic in Realistic Environments},
	booktitle = {Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on},
	year = {2016},
	pages = {1645{\textendash}1652},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Daejeon, South Korea},
	doi = {10.1109/IROS.2016.7759265},
	author = {Csaba Vir{\'a}gh and M{\'a}t{\'e} Nagy and Carlos Gershenson and G{\'a}bor V{\'a}s{\'a}rhelyi}
}
@article {Pina2016,
	title = {Towards a Standard Sampling Methodology on Online Social Networks: Collecting Global Trends on Twitter},
	journal = {Applied Network Science},
	volume = {1},
	year = {2016},
	pages = {3},
	doi = {10.1007/s41109-016-0004-1},
	url = {http://dx.doi.org/10.1007/s41109-016-0004-1},
	author = {C. A. Pi{\~n}a-Garc{\'\i}a and Carlos Gershenson and J. Mario Siqueiros-Garc{\'\i}a}
}
@article {160,
	title = {Complejidad, Tecnolog{\'\i}a y Sociedad},
	journal = {Investigaci{\'o}n y Ciencia},
	volume = {460},
	year = {2015},
	month = {Enero},
	pages = {48-54},
	url = {http://www.investigacionyciencia.es/revistas/investigacion-y-ciencia/numeros/2015/1/complejidad-tecnologa-y-sociedad-12732},
	author = {Carlos Gershenson}
}
@inbook {Gershenson2015CxMed,
	title = {Complejidad y medicina: perspectivas para el siglo XXI},
	booktitle = {Desaf{\'\i}os para la Salud P{\'u}blica},
	series = {Hacia d{\'o}nde va la Ciencia en M{\'e}xico},
	year = {2015},
	pages = {101{\textendash}111},
	publisher = {CONACYT, AMC, CCC},
	organization = {CONACYT, AMC, CCC},
	url = {http://www.ccciencias.mx/libroshdvcm/14.pdf},
	author = {Carlos Gershenson},
	editor = {Mario C{\'e}sar Salinas Carmona}
}
@article {154,
	title = {Complexity measurement of natural and artificial languages},
	journal = {Complexity},
	volume = {20},
	year = {2015},
	month = {July/August},
	pages = {25{\textendash}48},
	abstract = {We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization, and complexity based on specific diversity and message length.},
	doi = {10.1002/cplx.21529},
	url = {http://arxiv.org/abs/1311.5427},
	author = {Gerardo Febres and Klaus Jaffe and Carlos Gershenson}
}
@inbook {Gershenson:2011,
	title = {Enfrentando a la Complejidad: Predecir vs. Adaptar},
	booktitle = {Compl{\`e}xica: cervell, societat i llengua des de la transdisciplinarietat},
	year = {2015},
	pages = {25{\textendash}38},
	publisher = {Universitat de Barcelona},
	organization = {Universitat de Barcelona},
	chapter = {1},
	address = {Barcelona},
	abstract = {Una de las presuposiciones de la ciencia desde los tiempos de Galileo, Newton y Laplace ha sido la previsibilidad del mundo. Esta idea ha influido en los modelos cient{{\'\i}ficos y tecnol{\'o}gicos. Sin embargo, en las {\'u}ltimas d{\'e}cadas, el caos y la complejidad han mostrado que no todos los fen{\'o}menos son previsibles, a{\'u}n siendo {\'e}stos deterministas. Si el espacio de un problema es previsible, podemos en teor{{\'\i}a encontrar una soluci{\'o}n por optimizaci{\'o}n. No obstante, si el espacio de un problema no es previsible, o cambia m{\'a}s r{\'a}pido de lo que podemos optimizarlo, la optimizaci{\'o}n probablemente nos dar{\'a} una soluci{\'o}n obsoleta. Esto sucede con frecuencia cuando la soluci{\'o}n inmediata afecta el espacio del problema mismo. Una alternativa se encuentra en la adaptaci{\'o}n. Si dotamos a un sistema de {\'e}sta propiedad, {\'e}ste mismo podr{\'a} encontrar nuevas soluciones para situaciones no previstas.},
	url = {http://arxiv.org/abs/0905.4908},
	author = {Carlos Gershenson}
}
@inbook {152,
	title = {Hacia un sistema de salud autoorganizante y emergente},
	booktitle = {Estado del Arte de la Medicina 2013-2014: Las ciencias de la complejidad y la innovaci{\'o}n m{\'e}dica: Aplicaciones},
	year = {2015},
	pages = {245{\textendash}254},
	publisher = {Academia Nacional de Medicina},
	organization = {Academia Nacional de Medicina},
	address = {Mexico},
	author = {Carlos Gershenson},
	editor = {Enrique Ruelas Barajas and Ricardo Mansilla Corona}
}
@article {155,
	title = {Harnessing the Complexity of Education with Information Technology},
	journal = {Complexity},
	volume = {20},
	year = {2015},
	month = {May/June},
	pages = {13{\textendash}16},
	abstract = {Education at all levels is facing several challenges in most countries, such as low quality, high costs, lack of educators, and unsatisfied student demand. Traditional approaches are becoming unable to deliver the required education. Several causes for this inefficiency can be identified. I argue that beyond specific causes, the lack of effective education is related to complexity. However, information technology is helping us overcome this complexity.},
	doi = {10.1002/cplx.21536},
	url = {http://arxiv.org/abs/1402.2827},
	author = {Carlos Gershenson}
}
@inbook {156,
	title = {Modelling Complexity for Policy: Opportunities and Challenges},
	booktitle = {Handobook on Complexity and Public Policy},
	year = {2015},
	pages = {205-220},
	publisher = {Edward Elgar},
	organization = {Edward Elgar},
	chapter = {13},
	author = {Bruce Edmonds and Carlos Gershenson},
	editor = {Robert Geyer and Paul Cairney}
}
@article {159,
	title = {Requisite Variety, Autopoiesis, and Self-organization},
	journal = {Kybernetes},
	volume = {44},
	year = {2015},
	pages = {866{\textendash}873},
	author = {Carlos Gershenson}
}
@inbook {LugoGershensonComplex2012,
	title = {Decoding Road Networks into Ancient Routes: The Case of the Aztec Empire in Mexico},
	booktitle = {Proceedings of the Second International Conference on Complex Sciences: Theory and Applications {(COMPLEX 2012)}},
	series = {LNICST},
	volume = {126},
	year = {2014},
	pages = {228{\textendash}233},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin, Germany},
	doi = {10.1007/978-3-319-03473-7_20},
	url = {http://dx.doi.org/10.1007/978-3-319-03473-7_20},
	author = {Igor Lugo and Carlos Gershenson},
	editor = {Kristin Glass}
}
@inbook {153,
	title = {Dolor, placebos y complejidad},
	booktitle = {Actualidades en el manejo del dolor y cuidados paliativos},
	year = {2014},
	publisher = {Editorial Alfil},
	organization = {Editorial Alfil},
	chapter = {36},
	address = {Mexico},
	author = {Carlos Gershenson and Javier Rosado},
	editor = {Bistre-Coh{\'e}n, Sara}
}
@article {Gershenson2014Info-computatio,
	title = {Info-computationalism or Materialism? Neither and Both},
	journal = {Constructivist Foundations},
	volume = {9},
	number = {2},
	year = {2014},
	pages = {241{\textendash}242},
	abstract = {The limitations of materialism for studying cognition have motivated alternative epistemologies based on information and computation. I argue that these alternatives are also inherently limited and that these limits can only be overcome by considering materialism, info-computationalism, and cognition at the same time.},
	url = {http://www.univie.ac.at/constructivism/journal/9/2/241.gershenson},
	author = {Carlos Gershenson}
}
@inbook {Fernandez2013Information-Mea,
	title = {Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis},
	booktitle = {Guided Self-Organization: Inception},
	year = {2014},
	note = {In Press},
	pages = {19-51},
	publisher = {Springer},
	organization = {Springer},
	abstract = {<p>This chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization. Homeostasis reflects the stability of a system. Autopoiesis is defined as the ratio between the complexity of a system and the complexity of its environment. The proposed measures can be applied at different scales, which can be studied with multi-scale profiles.</p>
},
	url = {http://arxiv.org/abs/1304.1842},
	author = {Nelson Fern{\'a}ndez and Carlos Maldonado and Carlos Gershenson},
	editor = {Mikhail Prokopenko}
}
@article {Zubillaga2014Measuring-the-C,
	title = {Measuring the Complexity of Self-organizing Traffic Lights},
	journal = {Entropy},
	volume = {16},
	number = {5},
	year = {2014},
	pages = {2384{\textendash}2407},
	abstract = {We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby{\textquoteright}s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.},
	doi = {10.3390/e16052384},
	url = {http://dx.doi.org/10.3390/e16052384},
	author = {Dar{\'\i}o Zubillaga and Geovany Cruz and Luis Daniel Aguilar and Jorge Zapot{\'e}catl and Nelson Fern{\'a}ndez and Jos{\'e} Aguilar and David A. Rosenblueth and Carlos Gershenson}
}
@article {Gershenson2013The-Past-Presen,
	title = {The Past, Present and Future of Cybernetics and Systems Research},
	journal = {systema: connecting matter, life, culture and technology},
	volume = {1},
	number = {3},
	year = {2014},
	pages = {4{\textendash}13},
	abstract = {Cybernetics and Systems Research (CSR) were developed in the mid-twentieth century, offering the possibility of describing and comparing different phenomena using the same language. The concepts which originated in CSR have spread to practically all disciplines, many now used within the scientific study of complex systems. CSR has the potential to contribute to the solution of relevant problems, but the path towards this goal is not straightforward. This paper summarizes the ideas presented by the authors during a round table in 2012 on the past, present and future of CSR.},
	url = {http://arxiv.org/abs/1308.6317},
	author = {Carlos Gershenson and Peter Csermely and Peter Erdi and Helena Knyazeva and Alexander Laszlo}
}
@article {Gershenson2013hablarCx,
	title = {?{\textquoteleft}{C{\'o}mo} hablar de complejidad?},
	journal = {{Llengua, Societat i Comunicaci{\'o}},
	volume = {11},
	year = {2013},
	pages = {14{\textendash}19},
	abstract = {Resum En els {\'u}ltims anys s{\textquoteright}ha sentit parlar cada cop m{\'e}s de complexitat. Tot i aix{\`o}, com que hi ha una diversitat creixent de discursos sobre aquest tema, en lloc de generar coneixement, estem generant confusi{\'o}. En aquest article s{\textquoteright}ofereix una perspectiva per parlar clarament sobre complexitat des d{\textquoteright}un punt de vista epistemol{\`o}gic. Paraules clau: complexitat, epistemologia, context, emerg{\`e}ncia Resumen En a{\~n}os recientes hemos escuchado hablar m{\'a}s y m{\'a}s sobre complejidad. Pero pareciera que al haber una diversidad creciente de discursos sobre el tema, en lugar de generar conocimiento estamos generando confusi{\'o}n. En este art{{\'\i}culo se ofrece una perspectiva para hablar claramente sobre la complejidad desde un punto de vista epistemol{\'o}gico. Palabras clave: complejidad, epistemolog{{\'\i}a, contexto, emergencia  Abstract In recent years, we have heard more and more about complexity. However, it seems that given the increasing discourse divergence on this topic, instead of generating knowledge we are generating confusion. This paper offers a perspective to speak clearly about complexity from an epistemological point of view. Keywords: complexity, epistemology, context, emergence},
	url = {http://revistes.ub.edu/index.php/LSC/article/view/5682},
	author = {Carlos Gershenson}
}
@inbook {Gershenson2013Complexity,
	title = {Complexity},
	booktitle = {Encyclopedia of Philosophy and the Social Sciences},
	year = {2013},
	month = {April},
	publisher = {SAGE},
	organization = {SAGE},
	abstract = {The term complexity derives etymologically from the Latin plexus, which means interwoven. Intuitively, this implies that something complex is composed by elements that are difficult to separate. This difficulty arises from the relevant interactions that take place between components. This lack of separability is at odds with the classical scientific method - which has been used since the times of Galileo, Newton, Descartes, and Laplace - and has also influenced philosophy and engineering. In recent decades, the scientific study of complexity and complex systems has proposed a paradigm shift in science and philosophy, proposing novel methods that take into account relevant interactions.},
	url = {http://arxiv.org/abs/1109.0214},
	author = {Carlos Gershenson},
	editor = {Byron Kaldis}
}
@inbook {Gershenson2013Facing-Complexi,
	title = {Facing Complexity: Prediction vs. Adaptation},
	booktitle = {Complexity Perspectives on Language, Communication and Society},
	year = {2013},
	pages = {3-14},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {One of the presuppositions of science since the times of Galileo, Newton, Laplace, and Descartes has been the predictability of the world. This idea has strongly influenced scientific and technological models. However, in recent decades, chaos and complexity have shown that not every phenomenon is predictable, even if it is deterministic. If a problem space is predictable, in theory we can find a solution via optimization. Nevertheless, if a problem space is not predictable, or it changes too fast, very probably optimization will offer obsolete solutions. This occurs often when the immediate solution affects the problem itself. An alternative is found in adaptation. An adaptive system will be able to find by itself new solutions for unforeseen situations.},
	isbn = {978-3-642-32816-9},
	doi = {10.1007/978-3-642-32817-6},
	url = {http://arxiv.org/abs/1112.3843},
	author = {Carlos Gershenson},
	editor = {Massip, A. and A. Bastardas}
}
@article {Gershenson:2011e,
	title = {The Implications of Interactions for Science and Philosophy},
	journal = {Foundations of Science},
	volume = {Early View},
	year = {2013},
	abstract = {Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions{\textendash}-which reductionism neglects{\textendash}-are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply non-reductionism, non-materialism, non-predictability, non-Platonism, and non-nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.},
	doi = {10.1007/s10699-012-9305-8},
	url = {http://arxiv.org/abs/1105.2827},
	author = {Carlos Gershenson}
}
@article {Gershenson:2013,
	title = {Living in Living Cities},
	journal = {Artificial Life},
	volume = {In Press},
	year = {2013},
	abstract = {<p>This paper presents and overview of current and potential applications of living technology to urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, while self-organizing traffic lights are used as a case study of the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed.</p>
},
	keywords = {cities, Self-organization, traffic, transport},
	url = {http://arxiv.org/abs/1111.3659},
	author = {Carlos Gershenson}
}
@unpublished {Amoretti:2012,
	title = {Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems},
	year = {2013},
	note = {Submitted to Computer Networks},
	abstract = {Ultra-large scale (ULS) systems are becoming pervasive. They are inherently complex, which makes their design and control a challenge for traditional methods. Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. We evaluate the proposal with a ULS computing system provided with genetic adaptation mechanisms. We show the evolution of the system with stable and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, that correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less "aggressive", the system may be more stable, but the optimal performance may not be achieved.},
	url = {http://arxiv.org/abs/1207.6656},
	author = {Michele Amoretti and Carlos Gershenson}
}
@article {Gershenson2013Previniendo-enf,
	title = {Previniendo enfermedades cr{\'o}nico-degenerativas con vacunas sociales},
	journal = {Cirug{\'{\i}a y Cirujanos},
	volume = {81},
	number = {2},
	year = {2013},
	pages = {83-84},
	url = {http://tinyurl.com/cdswlx5},
	author = {Carlos Gershenson and Thomas Wisdom}
}
@article {GershensonRosenblueth:2010,
	title = {Adaptive self-organization vs. static optimization: A qualitative comparison in traffic light coordination},
	journal = {Kybernetes},
	volume = {41},
	number = {3},
	year = {2012},
	pages = {386-403},
	abstract = {Using a recently proposed model of city traffic based on elementary cellular automata, we compare qualitatively two methods for coordinating traffic lights: a \emph{green-wave} method that tries to optimize phases according to expected flows and a \emph{self-organizing} method that adapts to the current traffic conditions. The \emph{self-organizing} method delivers considerable improvements over the \emph{green-wave} method. Seven dynamical regimes and six phase transitions are identified and analyzed for the \emph{self-organizing} method. For low densities, the \emph{self-organizing} method promotes the formation and coordination of platoons that flow freely in four directions, i.e.\ with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high densities, the method prevents gridlocks and promotes the formation and coordination of {\textquoteleft}{\textquoteleft}free-spaces" that flow in the opposite direction of traffic.},
	doi = {10.1108/03684921211229479},
	url = {http://dx.doi.org/10.1108/03684921211229479},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@article {GershensonFernandez:2012,
	title = {Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales},
	journal = {Complexity},
	volume = {18},
	number = {2},
	year = {2012},
	pages = {29-44},
	abstract = {Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales.},
	doi = {10.1002/cplx.21424},
	url = {http://dx.doi.org/10.1002/cplx.21424},
	author = {Carlos Gershenson and Nelson Fern{\'a}ndez}
}
@article {Gershenson:2010,
	title = {Guiding the Self-organization of Random Boolean Networks},
	journal = {Theory in Biosciences},
	volume = {131},
	number = {3},
	year = {2012},
	month = {September},
	pages = {181-191},
	abstract = {Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews eight different methods for guiding the self-organization of RBNs. In particular, the article is focussed on guiding RBNs towards the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases. The properties and advantages of the critical regime for life, computation, adaptability, evolvability, and robustness are reviewed. The guidance methods of RBNs can be used for engineering systems with the features of the critical regime, as well as for studying how natural selection evolved living systems, which are also critical.},
	doi = {10.1007/s12064-011-0144-x},
	url = {http://arxiv.org/abs/1005.5733},
	author = {Carlos Gershenson}
}
@inbook {Edmonds:2012,
	title = {Learning, Social Intelligence and the {Turing} Test - why an {\textquoteleft}{\textquoteleft}out-of-the-box" {Turing} Machine will not pass the {Turing} Test.},
	booktitle = {How the world computes : Turing Centenary Conference and 8th Conference on Computability in Europe, CiE 2012, Cambridge, UK, June 18-23, 2012. Proceedings},
	series = {Lecture Notes in Computer Science},
	volume = {7318/2012},
	year = {2012},
	pages = {182{\textendash}192},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Berlin Heidelberg},
	abstract = {The Turing Test (TT) checks for human intelligence, rather than any putative general intelligence. It involves repeated interaction requiring learning in the form of adaption to the human conversation partner. It is a macro-level post-hoc test in contrast to the definition of a Turing Machine (TM), which is a prior micro-level definition. This raises the question of whether learning is just another computational process, i.e. can be implemented as a TM. Here we argue that learning or adaption is fundamentally different from computation, though it does involve processes that can be seen as computations. To illustrate this difference we compare (a) designing a TM and (b) learning a TM, defining them for the purpose of the argument. We show that there is a well-defined sequence of problems which are not effectively designable but are learnable, in the form of the bounded halting problem. Some characteristics of human intelligence are reviewed including it{\textquoteright}s: interactive nature, learning abilities, imitative tendencies, linguistic ability and context-dependency. A story that explains some of these is the Social Intelligence Hypothesis. If this is broadly correct, this points to the necessity of a considerable period of acculturation (social learning in context) if an artificial intelligence is to pass the TT. Whilst it is always possible to {\textquoteright}compile{\textquoteright} the results of learning into a TM, this would not be a designed TM and would not be able to continually adapt (pass future TTs). We conclude three things, namely that: a purely "designed" TM will never pass the TT; that there is no such thing as a general intelligence since it necessary involves learning; and that learning/adaption and computation should be clearly distinguished.},
	doi = {10.1007/978-3-642-30870-3_18},
	url = {http://arxiv.org/abs/1203.3376},
	author = {Bruce Edmonds and Carlos Gershenson},
	editor = {S. Barry Cooper and Anuj Dawar and Benedikt L{\"o}we}
}
@article {De-La-Guardia:2012,
	title = {Self-organizing systems on chip},
	journal = {Intel Technology Journal},
	volume = {16},
	number = {2},
	year = {2012},
	pages = {182{\textendash}201},
	abstract = {Self-organization in the context of computing systems refers to a technological approach to deal with the increasing complexity associated with the deployment, maintenance, and evolution of such systems. The terms self-organizing and autonomous are often used interchangeably in relation to systems that use organic principles (self-configuration, self-healing, and so on) in their design and operation. In the specific case of system on chip (SoC) design, organic principles are clearly in the solution path for some of the most important challenges in areas like logic organization, data movement, circuits, and software[47]. In this article, we start by providing a definition of the concept of self-organization as it applies to SoCs, explaining what it means and how it may be applied. We then provide a survey of the various recent papers, journal articles, and books on the subject and close by pointing out possible future directions, challenges and opportunities for self-organizing SoCs.},
	url = {http://noggin.intel.com/technology-journal/2012/162/exploring-control-and-autonomic-computing},
	author = {Rafael {De La Guardia} and Carlos Gershenson}
}
@article {GershensonRosenblueth:2011,
	title = {Self-organizing traffic lights at multiple-street intersections},
	journal = {Complexity},
	volume = {17},
	number = {4},
	year = {2012},
	pages = {23-39},
	abstract = {The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. This automaton can therefore model highway traffic. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios employing an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic light controller for a grid of six-way streets allowing for either two or three street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the {\textquoteleft}{\textquoteleft}green wave{\textquoteright}{\textquoteright} method). We observe a tradeoff between system capacity and topological complexity. The green wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this paper we propose a benchmark, independent of methods and models, to measure the performance of a traffic light controller comparing it against a theoretical optimum.},
	doi = {10.1002/cplx.20395},
	url = {http://dx.doi.org/10.1002/cplx.20395},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@inbook {Gershenson:2011b,
	title = {Self-organizing urban transportation systems},
	booktitle = {Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design},
	year = {2012},
	pages = {269-279},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete solutions, as the problem changes before it can be optimized. An alternative lies in seeking adaptive solutions. This adaptation can be achieved with self-organization. In a self-organizing transportation system, the elements of the system follow local rules to achieve a global solution. Like this, when the problem changes the system can adapt by itself to the new configuration. In this chapter, I will review recent, current, and future work on self-organizing transportation systems. Self-organizing traffic lights have proven to improve traffic flow considerably over traditional methods. In public transportation systems, simple rules are being explored to prevent the "equal headway instability" phenomenon. The methods we have used can be also applied to other urban transportation systems and their generality is discussed.},
	doi = {10.1007/978-3-642-24544-2_15},
	url = {http://arxiv.org/abs/0912.1588},
	author = {Carlos Gershenson},
	editor = {Juval Portugali and Han Meyer and Egbert Stolk and Ekim Tan}
}
@conference {Fernandez:2012,
	title = {Sistemas Din{\'a}micos como Redes Computacionales de Agentes para la evaluaci{\'o}n de sus Propiedades Emergentes.},
	booktitle = {II Simposio Cient{\'{\i}fico y Tecnol{\'o}gico en Computaci{\'o}n SCTC 2012},
	year = {2012},
	address = {Universidad Central de Venezuela},
	author = {Nelson Fern{\'a}ndez and Jos{\'e} Aguilar and Carlos Gershenson and Oswaldo Ter{\'a}n}
}
@inbook {Gershenson:2007,
	title = {The World as Evolving Information},
	booktitle = {Unifying Themes in Complex Systems},
	volume = {VII},
	year = {2012},
	pages = {100-115},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex. The paper presents five tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, and complexity principles. These are further used to discuss the notions of life and cognition and their evolution.},
	doi = {10.1007/978-3-642-18003-3_10},
	url = {http://arxiv.org/abs/0704.0304},
	author = {Carlos Gershenson},
	editor = {Minai, Ali and Braha, Dan and Yaneer {Bar-Yam}}
}
@article {GershensonProkopenko:2011,
	title = {Complex Networks},
	journal = {Artificial Life},
	volume = {17},
	number = {4},
	year = {2011},
	month = {Fall},
	pages = {259{\textendash}261},
	publisher = {MIT Press},
	abstract = {Introduction to the Special Issue on Complex Networks, Artificial Life journal.},
	doi = {10.1162/artl_e_00037},
	url = {http://arxiv.org/abs/1104.5538},
	author = {Carlos Gershenson and Mikhail Prokopenko}
}
@inbook {Gershenson:2011,
	title = {Enfrentando a la Complejidad: Predecir vs. Adaptar},
	booktitle = {Complejidad y Lenguaje},
	year = {2011},
	note = {In Press},
	abstract = {Una de las presuposiciones de la ciencia desde los tiempos de Galileo, Newton y Laplace ha sido la previsibilidad del mundo. Esta idea ha influido en los modelos cient{\'{\i}ficos y tecnol{\'o}gicos. Sin embargo, en las {\'u}ltimas d{\'e}cadas, el caos y la complejidad han mostrado que no todos los fen{\'o}menos son previsibles, a{\'u}n siendo {\'e}stos deterministas. Si el espacio de un problema es previsible, podemos en teor{\'{\i}a encontrar una soluci{\'o}n por optimizaci{\'o}n. No obstante, si el espacio de un problema no es previsible, o cambia m{\'a}s r{\'a}pido de lo que podemos optimizarlo, la optimizaci{\'o}n probablemente nos dar{\'a} una soluci{\'o}n obsoleta. Esto sucede con frecuencia cuando la soluci{\'o}n inmediata afecta el espacio del problema mismo. Una alternativa se encuentra en la adaptaci{\'o}n. Si dotamos a un sistema de {\'e}sta propiedad, {\'e}ste mismo podr{\'a} encontrar nuevas soluciones para situaciones no previstas.},
	url = {http://arxiv.org/abs/0905.4908},
	author = {Carlos Gershenson},
	editor = {Martorell, X. and Massip, A.}
}
@article {Gershenson:2011c,
	title = {Epidemiolog{\'{\i}a y las Redes Sociales},
	journal = {Cirug{\'{\i}a y Cirujanos},
	volume = {79},
	number = {3},
	year = {2011},
	pages = {199-200},
	url = {http://tinyurl.com/7nmt3p9},
	author = {Carlos Gershenson}
}
@article {RosenbluethGershenson:2010,
	title = {A model of city traffic based on elementary cellular automata},
	journal = {Complex Systems},
	volume = {19},
	number = {4},
	year = {2011},
	pages = {305-322},
	abstract = {There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136.},
	url = {http://www.complex-systems.com/pdf/19-4-1.pdf},
	author = {David A. Rosenblueth and Carlos Gershenson}
}
@article {BalpoGershenson:2011,
	title = {Modular Random {Boolean} Networks},
	journal = {Artificial Life},
	volume = {17},
	number = {4},
	year = {2011},
	pages = {331{\textendash}351},
	publisher = {MIT Press},
	abstract = {Random Boolean networks (RBNs) have been a popular model of genetic regulatory networks for more than four decades. However, most RBN studies have been made with random topologies, while real regulatory networks have been found to be modular. In this work, we extend classical RBNs to define modular RBNs. Statistical experiments and analytical results show that modularity has a strong effect on the properties of RBNs. In particular, modular RBNs have more attractors and are closer to criticality when chaotic dynamics would be expected, compared to classical RBNs.},
	doi = {10.1162/artl_a_00042},
	url = {http://arxiv.org/abs/1101.1893},
	author = {Rodrigo {Poblanno-Balp} and Carlos Gershenson}
}
@inbook {GershensonHeylighen2004,
	title = {Protocol Requirements for Self-Organizing Artifacts: Towards an Ambient Intelligence},
	booktitle = {Unifying Themes in Complex Systems},
	volume = {V},
	year = {2011},
	note = {Also VUB AI-Lab Memo 04-04},
	pages = {136-143},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {We discuss which properties common-use artifacts should have to collaborate without human intervention. We conceive how devices, such as mobile phones, PDAs, and home appliances, could be seamlessly integrated to provide an "ambient intelligence" that responds to the users desires without requiring explicit programming or commands. While the hardware and software technology to build such systems already exists, yet there is no protocol to direct and give meaning to their interactions. We propose the first steps in the development of such a protocol, which would need to be adaptive, extensible, and open to the community, while promoting self-organization. We argue that devices, interacting through "game-like" moves, can learn to agree about how to communicate, with whom to cooperate, and how to delegate and coordinate specialized tasks. Like this, they may evolve distributed cognition or collective intelligence able to tackle any complex of tasks.},
	doi = {10.1007/978-3-642-17635-7_17},
	url = {http://arxiv.org/abs/nlin.AO/0404004},
	author = {Carlos Gershenson and Francis Heylighen},
	editor = {Minai, Ali and Braha, Dan and Yaneer {Bar-Yam}}
}
@article {Gershenson:2011a,
	title = {Self-organization leads to supraoptimal performance in public transportation systems},
	journal = {{PLoS ONE}},
	volume = {6},
	number = {6},
	year = {2011},
	pages = {e21469},
	abstract = {The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a {\textquoteleft}{\textquoteleft}slower-is-faster{\textquoteright}{\textquoteright} effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses {\textquoteleft}{\textquoteleft}antipheromones{\textquoteright}{\textquoteright} to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies.},
	doi = {10.1371/journal.pone.0021469},
	url = {http://dx.doi.org/10.1371/journal.pone.0021469},
	author = {Carlos Gershenson}
}
@book {IWSOS2011,
	title = {Self-Organizing Systems 5th International Workshop, IWSOS 2011, Karlsruhe, Germany, February 23-24, 2011, Proceedings. Springer LNCS 6557},
	series = {Lecture Notes in Computer Science},
	volume = {6557},
	year = {2011},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This book constitutes the refereed proceedings of the 5th International Workshop on Self-Organizing Systems, IWSOS 2011, held in Karlsruhe, Germany, in February 2011. The 9 revised full papers presented together with 1 invited paper were carefully selected from 25 initial submissions. It was the 5th workshop in a series of multidisciplinary events dedicated to self-organization in networked systems with main focus on communication and computer networks. The papers address theoretical aspects of self-organization as well as applications in communication and computer networks and robot networks.},
	isbn = {978-3-642-19166-4},
	doi = {10.1007/978-3-642-19167-1},
	url = {http://dx.doi.org/10.1007/978-3-642-19167-1},
	editor = {Christian Bettstetter and Carlos Gershenson}
}
@article {Gershenson:2010a,
	title = {The Sigma Profile: A Formal Tool to Study Organization and its Evolution at Multiple Scales},
	journal = {Complexity},
	volume = {16},
	number = {5},
	year = {2011},
	pages = {37-44},
	abstract = {The σ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal-oriented agents, one can define σ ∈ [0,1] (satisfaction) as the degree to which the goals of each agent at each scale have been met. σ reflects the organization degree at that scale. The σ profile of a system shows the satisfaction at different scales, with the possibility to study their dependencies and evolution. It can also be used to extend game theoretic models. The description of a general tendency on the evolution of complexity and cooperation naturally follows from the σ profile. Experiments on a virtual ecosystem are used as illustration.},
	doi = {10.1002/cplx.20350},
	url = {http://arxiv.org/abs/0809.0504},
	author = {Carlos Gershenson}
}
@article {Gershenson:2011d,
	title = {What does artificial life tell us about death?},
	journal = {International Journal of Artificial Life Research},
	volume = {2},
	number = {3},
	year = {2011},
	pages = {1-5},
	abstract = {Short philosophical essay},
	url = {http://arxiv.org/abs/0906.2824},
	author = {Carlos Gershenson}
}
@article {Gershenson:2010b,
	title = {Computing Networks: A General Framework to Contrast Neural and Swarm Cognitions},
	journal = {Paladyn, Journal of Behavioral Robotics},
	volume = {1},
	number = {2},
	year = {2010},
	pages = {147-153},
	abstract = {This paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures. Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs. The description of these architectures as CNs allows their comparison. Their differences and similarities allow the identification of properties that enable neural and swarm architectures to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales. The relationship between multiple dynamical and functional scales with adaptation, cognition (of brains and swarms) and computation is discussed.},
	doi = {10.2478/s13230-010-0015-z},
	url = {http://dx.doi.org/10.2478/s13230-010-0015-z},
	author = {Carlos Gershenson}
}
@inbook {BalpoGershenson:2010,
	title = {Modular Random {Boolean} Networks},
	booktitle = {{Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems},
	year = {2010},
	pages = {303-304},
	publisher = {MIT Press},
	organization = {MIT Press},
	address = {Odense, Denmark},
	url = {http://mitpress.mit.edu/books/chapters/0262290758chap56.pdf},
	author = {Rodrigo {Poblanno-Balp} and Carlos Gershenson},
	editor = {Harold Fellermann and Mark D{\"o}rr and Martin M. Hanczyc and Lone Ladegaard Laursen and Sarah Maurer and Daniel Merkle and Pierre-Alain Monnard and Kasper St${\o}$y and Steen Rasmussen}
}
@unpublished {GershensonRosenblueth2009,
	title = {Modeling self-organizing traffic lights with elementary cellular automata},
	year = {2009},
	note = {Submitted},
	abstract = {There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136. The simplicity of the model offers a clear understanding of the main properties of city traffic and its phase transitions. We use the proposed model to compare two methods for coordinating traffic lights: a green-wave method that tries to optimize phases according to expected flows and a self-organizing method that adapts to the current traffic conditions. The self-organizing method delivers considerable improvements over the green-wave method. For low densities, the self-organizing method promotes the formation and coordination of platoons that flow freely in four directions, i.e. with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high densities, the method prevents gridlocks and promotes the formation and coordination of "free-spaces" that flow in the opposite direction of traffic.},
	url = {http://arxiv.org/abs/0907.1925},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@article {GershensonPineda2009,
	title = {Why does public transport not arrive on time? The pervasiveness of equal headway instability},
	journal = {{PLoS ONE}},
	volume = {4},
	number = {10},
	year = {2009},
	pages = {e7292},
	abstract = {Background The equal headway instability phenomenon is pervasive in public transport systems. This instability is characterized by an aggregation of vehicles that causes inefficient service. While equal headway instability is common, it has not been studied independently of a particular scenario. However, the phenomenon is apparent in many transport systems and can be modeled and rectified in abstraction. Methodology We present a multi-agent simulation where a default method with no restrictions always leads to unstable headways. We discuss two methods that attempt to achieve equal headways, called minimum and maximum. Since one parameter of the methods depends on the passenger density, adaptive versions{\textendash}-where the relevant parameter is adjusted automatically{\textendash}-are also put forward. Our results show that the adaptive maximum method improves significantly over the default method. The model and simulation give insights of the interplay between transport design and passenger behavior. Finally, we provide technological and social suggestions for engineers and passengers to help achieve equal headways and thus reduce delays. Conclusions The equal headway instability phenomenon can be avoided with the suggested technological and social measures.},
	doi = {10.1371/journal.pone.0007292},
	url = {http://dx.doi.org/10.1371/journal.pone.0007292},
	author = {Carlos Gershenson and Luis A. Pineda}
}
@book {Cx5Q,
	title = {Complexity: 5 Questions},
	year = {2008},
	publisher = {Automatic Peess / VIP},
	organization = {Automatic Peess / VIP},
	isbn = {8792130135},
	url = {http://tinyurl.com/ovg3jn},
	editor = {Carlos Gershenson}
}
@article {GershensonLenaerts2008,
	title = {Evolution of Complexity},
	journal = {Artificial Life},
	volume = {14},
	number = {3},
	year = {2008},
	note = {Special Issue on the Evolution of Complexity},
	month = {Summer},
	pages = {1{\textendash}3},
	doi = {10.1162/artl.2008.14.3.14300},
	url = {http://dx.doi.org/10.1162/artl.2008.14.3.14300},
	author = {Carlos Gershenson and Tom Lenaerts}
}
@article {GershensonSOBs,
	title = {Towards Self-organizing Bureaucracies},
	journal = {International Journal of Public Information Systems},
	volume = {2008},
	number = {1},
	year = {2008},
	pages = {1{\textendash}24},
	abstract = {The goal of this paper is to contribute to eGovernment efforts, encouraging the use of self-organization as a method to improve the efficiency and adaptability of bureaucracies and similar social systems. Bureaucracies are described as networks of agents, where the main design principle is to reduce local "friction" to increase local and global "satisfaction". Following this principle, solutions are proposed for improving communication within bureaucracies, sensing public satisfaction, dynamic modification of hierarchies, and contextualization of procedures. Each of these reduces friction between agents (internal or external), increasing the efficiency of bureaucracies. Current technologies can be applied for this end. "Random agent networks" (RANs), novel computational models, are introduced to illustrate the benefits of self-organizing bureaucracies. Simulations show that only few changes are required to reach near-optimal performance, potentially adapting quickly and effectively to shifts in demand.},
	url = {http://www.ijpis.net/issues/no1_2008/no1_2008_p1.htm},
	author = {Carlos Gershenson}
}
@inbook {HeylighenEtAl2007,
	title = {Complexity and Philosophy},
	booktitle = {Complexity, Science and Society},
	year = {2007},
	pages = {117-134},
	publisher = {Radcliffe Publishing},
	organization = {Radcliffe Publishing},
	address = {Oxford},
	url = {http://arxiv.org/abs/cs.CC/0604072},
	author = {Francis Heylighen and Paul Cilliers and Carlos Gershenson},
	editor = {Jan Bogg and Robert Geyer}
}
@book {GershensonDCSOS,
	title = {Design and Control of Self-organizing Systems},
	year = {2007},
	note = {http://tinyurl.com/DCSOS2007},
	publisher = {CopIt Arxives},
	organization = {CopIt Arxives},
	address = {Mexico},
	abstract = {Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I pro- pose a methodology to aid engineers in the design and control of com- plex systems. This is based on the description of systems as self- organizing. Starting from the agent metaphor, the methodology pro- poses a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by ac- tively interacting among themselves. The main premise of the method- ology claims that reducing the "friction" of interactions between el- ements of a system will result in a higher "satisfaction" of the system, i.e. better performance. A general introduction to complex thinking is given, since designing self-organizing systems requires a non-classical thought, while prac- tical notions of complexity and self-organization are put forward. To illustrate the methodology, I present three case studies. Self-organizing traffic light controllers are proposed and studied with multi-agent simulations, outperforming traditional methods. Methods for im- proving communication within self-organizing bureaucracies are ad- vanced, introducing a simple computational model to illustrate the benefits of self-organization. In the last case study, requirements for self-organizing artifacts in an ambient intelligence scenario are dis- cussed. Philosophical implications of the conceptual framework are also put forward.},
	keywords = {Complexity Theory, Physics, Self-organization},
	isbn = {978-0-9831172-3-0},
	url = {http://tinyurl.com/DCSOS2007},
	author = {Carlos Gershenson}
}
@mastersthesis {GershensonPhD,
	title = {Design and Control of Self-organizing Systems},
	year = {2007},
	month = {May},
	school = {Vrije Universiteit Brussel},
	type = {phd},
	address = {Brussels, Belgium},
	abstract = {Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this thesis I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves. The main premise of the methodology claims that reducing the {\textquoteleft}{\textquoteleft}friction{\textquoteright}{\textquoteright} of interactions between elements of a system will result in a higher {\textquoteleft}{\textquoteleft}satisfaction{\textquoteright}{\textquoteright} of the system, i.e. better performance. A general introduction to complex thinking is given, since designing self-organizing systems requires a non-classical thought, while practical notions of complexity and self-organization are put forward. To illustrate the methodology, I present three case studies. Self-organizing traffic light controllers are proposed and studied with multi-agent simulations, outperforming traditional methods. Methods for improving communication within self-organizing bureaucracies are advanced, introducing a simple computational model to illustrate the benefits of self-organization. In the last case study, requirements for self-organizing artifacts in an ambient intelligence scenario are discussed. Philosophical implications of the conceptual framework are also put forward.},
	url = {http://cogprints.org/5442/},
	author = {Carlos Gershenson}
}
@book {GershensonEtAl-PnC,
	title = {Philosophy and Complexity},
	series = {Worldviews, Science and Us},
	year = {2007},
	publisher = {World Scientific},
	organization = {World Scientific},
	address = {Singapore},
	abstract = {Scientific, technological, and cultural changes have always had an impact upon philosophy. They can force a change in the way we perceive the world, reveal new kinds of phenomena to be understood, and provide new ways of understanding phenomena. Complexity science, immersed in a culture of information, is having a diverse but particularly significant impact upon philosophy. Previous ideas do not necessarily sit comfortably with the new paradigm, resulting in new ideas or new interpretations of old ideas. In this unprecedented interdisciplinary volume, researchers from different backgrounds join efforts to update thinking upon philosophical questions with developments in the scientific study of complex systems. The contributions focus on a wide range of topics, but share the common goal of increasing our understanding and improving our descriptions of our complex world. This revolutionary debate includes contributions from leading experts, as well as young researchers proposing fresh ideas.},
	url = {http://www.worldscibooks.com/chaos/6372.html},
	editor = {Carlos Gershenson and Diederik Aerts and Bruce Edmonds}
}
@inbook {CoolsEtAl2007,
	title = {Self-organizing traffic lights: A realistic simulation},
	booktitle = {Self-Organization: Applied Multi-Agent Systems},
	year = {2007},
	pages = {41{\textendash}49},
	publisher = {Springer},
	organization = {Springer},
	chapter = {3},
	abstract = {We have previously shown in an abstract simulation (Gershenson, 2005) that self-organizing traffic lights can improve greatly traffic flow for any density. In this paper, we extend these results to a realistic setting, implementing self-organizing traffic lights in an advanced traffic simulator using real data from a Brussels avenue. On average, for different traffic densities, travel waiting times are reduced by 50\% compared to the current green wave method.},
	doi = {10.1007/978-1-84628-982-8_3},
	url = {http://arxiv.org/abs/nlin.AO/0610040},
	author = {Seung Bae Cools and Carlos Gershenson and Bart {D{\textquoteright}Hooghe}},
	editor = {Mikhail Prokopenko}
}
@inbook {Gershenson2007-SOS,
	title = {Towards a General Methodology for Designing Self-Organizing Systems},
	booktitle = {Complexity, Science and Society},
	year = {2007},
	publisher = {Radcliffe Publishing},
	organization = {Radcliffe Publishing},
	address = {Oxford},
	author = {Carlos Gershenson},
	editor = {Jan Bogg and Robert Geyer}
}
@conference {GershensonLenaerts2006,
	title = {Evolution of Complexity: Introduction to the Workshop},
	booktitle = {{ALife X} Workshop Proceedings},
	year = {2006},
	pages = {71{\textendash}72},
	url = {http://uk.arxiv.org/abs/nlin.AO/0604069},
	author = {Carlos Gershenson and Tom Lenaerts}
}
@booklet {Gershenson2006,
	title = {A General Methodology for Designing Self-Organizing Systems},
	number = {2005-05},
	year = {2006},
	publisher = {ECCO},
	url = {http://uk.arxiv.org/abs/nlin.AO/0505009},
	author = {Carlos Gershenson}
}
@conference {GershensonEtAl2006,
	title = {The Role of Redundancy in the Robustness of Random {Boolean} Networks},
	booktitle = {{Artificial Life X}, Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems.},
	year = {2006},
	pages = {35{\textendash}42},
	publisher = {MIT Press},
	organization = {MIT Press},
	abstract = {Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes. In this paper, we study the effect that redundant nodes have on the robustness of RBNs. Using computer simulations, we have found that the addition of redundant nodes to RBNs increases their robustness. We conjecture that redundancy is a way of "smoothening" fitness landscapes. Therefore, redundancy can facilitate evolutionary searches. However, too much redundancy could reduce the rate of adaptation of an evolutionary process. Our results also provide supporting evidence in favour of Kauffman{\textquoteright}s conjecture (Kauffman, 2000, p.195).},
	url = {http://uk.arxiv.org/abs/nlin.AO/0511018},
	author = {Carlos Gershenson and Stuart A. Kauffman and Ilya Shmulevich},
	editor = {Rocha, L. M. and L. S. Yaeger and M. A. Bedau and D. Floreano and R. L. Goldstone and A. Vespignani}
}
@inbook {GershensonHeylighen2005,
	title = {How Can We Think the Complex?},
	booktitle = {Managing Organizational Complexity: Philosophy, Theory and Application},
	year = {2005},
	pages = {47{\textendash}61},
	publisher = {Information Age Publishing},
	organization = {Information Age Publishing},
	chapter = {3},
	abstract = {This chapter does not deal with specific tools and techniques for managing complex systems, but proposes some basic concepts that help us to think and speak about complexity. We review classical thinking and its intrinsic drawbacks when dealing with complexity. We then show how complexity forces us to build models with indeterminacy and unpredictability. However, we can still deal with the problems created in this way by being adaptive, and profiting from a complex system{\textquoteright}s capability for selforganization, and the distributed intelligence this may produce.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0402023},
	author = {Carlos Gershenson and Francis Heylighen},
	editor = {Kurt Richardson}
}
@article {Gershenson2005,
	title = {Self-Organizing Traffic Lights},
	journal = {Complex Systems},
	volume = {16},
	number = {1},
	year = {2005},
	pages = {29{\textendash}53},
	abstract = {Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem. We propose a simple and feasible alternative, in which traffic lights self-organize to improve traffic flow. We use a multi-agent simulation to study three self-organizing methods, which are able to outperform traditional rigid and adaptive methods. Using simple rules and no direct communication, traffic lights are able to self-organize and adapt to changing traffic conditions, reducing waiting times, number of stopped cars, and increasing average speeds.},
	url = {http://www.complex-systems.com/pdf/16-1-2.pdf},
	author = {Carlos Gershenson}
}
@article {Gershenson2004,
	title = {Cognitive Paradigms: Which One is the Best?},
	journal = {Cognitive Systems Research},
	volume = {5},
	number = {2},
	year = {2004},
	month = {June},
	pages = {135{\textendash}156},
	abstract = {I discuss the suitability of different paradigms for studying cognition. I use a virtual laboratory that implements five different representative models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no "best" model, since different models are better for different things in different contexts. Using the results as an empirical philosophical aid, I note that there is no "best" approach for studying cognition, since different paradigms have all advantages and disadvantages, since they study different aspects of cognition from different contexts. This has implications for current debates on "proper" approaches for cognition: all approaches are a bit proper, but none will be "proper enough". I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition.},
	url = {http://dx.doi.org/10.1016/j.cogsys.2003.10.002},
	author = {Carlos Gershenson}
}
@conference {Gershenson2004c,
	title = {Introduction to Random {Boolean} Networks},
	booktitle = {Workshop and Tutorial Proceedings, Ninth International Conference on the Simulation and Synthesis of Living Systems {(ALife} {IX)}},
	year = {2004},
	pages = {160{\textendash}173},
	address = {Boston, MA},
	abstract = {The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic. The tutorial, intended for a broad audience, presents the state of the art in RBNs, spanning over several lines of research carried out by different groups. We focus on research done within artificial life, as we cannot exhaust the abundant research done over the decades related to RBNs.},
	url = {http://arxiv.org/abs/nlin.AO/0408006},
	author = {Carlos Gershenson},
	editor = {M. Bedau and P. Husbands and T. Hutton and S. Kumar and H. Suzuki}
}
@unpublished {Gershenson2004a,
	title = {Phase Transitions in Random {Boolean} Networks with Different Updating Schemes},
	year = {2004},
	note = {Unpublished},
	abstract = {In this paper we study the phase transitions of different types of Random Boolean networks. These differ in their updating scheme: synchronous, semi-synchronous, or asynchronous, and deterministic or non-deterministic. It has been shown that the statistical properties of Random Boolean networks change considerable according to the updating scheme. We study with computer simulations sensitivity to initial conditions as a measure of order/chaos. We find that independently of their updating scheme, all network types have very similar phase transitions, namely when the average number of connections of nodes is between one and three. This critical value depends more on the size of the network than on the updating scheme.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0311008},
	author = {Carlos Gershenson}
}
@conference {Gershenson2004b,
	title = {Updating Schemes in Random {Boolean} Networks: Do They Really Matter?},
	booktitle = {Artificial Life {IX} Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems},
	year = {2004},
	pages = {238{\textendash}243},
	publisher = {MIT Press},
	organization = {MIT Press},
	abstract = {In this paper we try to end the debate concerning the suitability of different updating schemes in random Boolean networks (RBNs). We quantify for the first time loose attractors in asyncrhonous RBNs, which allows us to analyze the complexity reduction related to different updating schemes. We also report that all updating schemes yield very similar critical stability values, meaning that the "edge of chaos" does not depend much on the updating scheme. After discussion, we conclude that synchonous RBNs are justifiable theoretical models of biological networks.},
	url = {http://arxiv.org/abs/nlin.AO/0402006},
	author = {Carlos Gershenson},
	editor = {J. Pollack and M. Bedau and P. Husbands and T. Ikegami and R. A. Watson}
}
@conference {Gershenson2003IJCAI,
	title = {Comparing Different Cognitive Paradigms with a Virtual Laboratory},
	booktitle = {{IJCAI}-03: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence},
	year = {2003},
	pages = {1635{\textendash}1636},
	publisher = {Morgan Kaufmann},
	organization = {Morgan Kaufmann},
	abstract = {A public virtual laboratory is presented, where animats are controlled by mechanisms from different cognitive paradigms. A brief description of the characteristics of the laboratory and the uses it has had is given. Mainly, it has been used to contrast philosophical ideas related with the notion of cognition, and to elucidate debates on "proper" paradigms in AI and cognitive science.},
	author = {Carlos Gershenson}
}
@conference {GershensonEtAl2003a,
	title = {Contextual Random {Boolean} Networks},
	booktitle = {Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801},
	year = {2003},
	pages = {615{\textendash}624},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	abstract = {We propose the use of Deterministic Generalized Asynchronous Random Boolean Networks (Gershenson, 2002) as models of contextual deterministic discrete dynamical systems. We show that changes in the context have drastic effects on the global properties of the same networks, namely the average number of attractors and the average percentage of states in attractors. We introduce the situation where we lack knowledge on the context as a more realistic model for contextual dynamical systems. We notice that this makes the network non-deterministic in a specific way, namely introducing a non-Kolmogorovian quantum-like structure for the modelling of the network (Aerts 1986). In this case, for example, a state of the network has the potentiality (probability) of collapsing into different attractors, depending on the specific form of lack of knowledge on the context.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0303021},
	author = {Carlos Gershenson and Jan Broekaert and Diederik Aerts},
	editor = {Banzhaf, W and T. Christaller and P. Dittrich and J. T. Kim and J. Ziegler}
}
@article {HeylighenGershenson2003,
	title = {The Meaning of Self-Organization in Computing},
	journal = {IEEE Intelligent Systems},
	year = {2003},
	month = {July/August},
	pages = {72{\textendash}75},
	url = {http://pcp.vub.ac.be/Papers/IEEE.Self-organization.pdf},
	author = {Francis Heylighen and Carlos Gershenson}
}
@unpublished {Gershenson2003u,
	title = {Self-organizing Traffic Control: First Results},
	year = {2003},
	note = {Unpublished},
	abstract = {We developed a virtual laboratory for traffic control where agents use different strategies in order to self-organize on the road. We present our first results where we compare the performance and behaviour promoted by environmental constrains and five different simple strategies: three inspired in flocking behaviour, one selfish, and one inspired in the minority game. Experiments are presented for comparing the strategies. Different issues are discussed, such as the important role of environmental constrains and the emergence of traffic lanes.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0309039},
	author = {Carlos Gershenson}
}
@conference {GershensonHeylighen2003a,
	title = {When Can We Call a System Self-Organizing?},
	booktitle = {Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801},
	year = {2003},
	pages = {606{\textendash}614},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin},
	abstract = {We do not attempt to provide yet another definition of self-organizing systems, nor review previous definitions. We explore the conditions necessary to describe self-organizing systems, inspired on decades of their study, in order to understand them better. These involve the dynamics of the system, and the purpose, boundaries, and description level chosen by an observer. We show how, changing the level or {\textquoteleft}{\textquoteleft}graining{\textquoteright}{\textquoteright} of description, the same system can be self-organizing or not. We also discuss common problems we face when studying self-organizing systems. We analyse when building, designing, and controlling artificial self-organizing systems is useful. We state that self-organization is a way of observing systems, not a class of systems.},
	url = {http://arxiv.org/abs/nlin.AO/0303020},
	author = {Carlos Gershenson and Francis Heylighen},
	editor = {Banzhaf, W and T. Christaller and P. Dittrich and J. T. Kim and J. Ziegler}
}
@unpublished {Gershenson2002uc,
	title = {Adaptive Development of Koncepts in Virtual Animats: Insights Into the Development of Knowledge},
	year = {2002},
	note = {Adaptive Systems Essay, COGS, University of Sussex},
	abstract = {As a part of our effort for studying the evolution and development of cognition, we present results derived from synthetic experimentations in a virtual laboratory where animats develop koncepts adaptively and ground their meaning through action. We introduce the term "koncept" to avoid confusions and ambiguity derived from the wide use of the word "concept". We present the models which our animats use for abstracting koncepts from perceptions, plastically adapt koncepts, and associate koncepts with actions. On a more philosophical vein, we suggest that knowledge is a property of a cognitive system, not an element, and therefore observer-dependent.},
	url = {http://uk.arxiv.org/abs/cs/0211027},
	author = {Carlos Gershenson}
}
@conference {Gershenson2002c,
	title = {Behaviour-Based Knowledge Systems: An Epigenetic Path from Behaviour to Knowledge},
	booktitle = {Proceedings of the 2nd Workshop on Epigenetic Robotics},
	volume = {94},
	year = {2002},
	pages = {35{\textendash}41},
	publisher = {Lund University Cognitive Studies},
	organization = {Lund University Cognitive Studies},
	address = {Edinburgh, Scotland},
	abstract = {In this paper we expose the theoretical background underlying our current research. This consists in the development of behaviour-based knowledge systems, for closing the gaps between behaviour-based and knowledge-based systems, and also between the understandings of the phenomena they model. We expose the requirements and stages for developing behaviour-based knowledge systems and discuss their limits. We believe that these are necessary conditions for the development of higher order cognitive capacities, in artificial and natural cognitive systems.},
	url = {http://www.lucs.lu.se/ftp/pub/LUCS\%5FStudies/LUCS94/Gershenson.pdf},
	author = {Carlos Gershenson},
	editor = {Christopher G. Prince and Yiannis Demiris and Yuval Marom and Hideki Kozima and Christian Balkenius}
}
@conference {Gershenson2002e,
	title = {Classification of Random {Boolean} Networks},
	booktitle = {Artificial Life {VIII}: Proceedings of the Eight International Conference on Artificial Life},
	year = {2002},
	pages = {1{\textendash}8},
	publisher = {MIT Press},
	organization = {MIT Press},
	address = {Cambridge, MA, USA},
	abstract = {We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena.},
	url = {http://arxiv.org/abs/cs/0208001},
	author = {Carlos Gershenson},
	editor = {Standish, R. K. and M. A. Bedau and H. A. Abbass}
}
@mastersthesis {Gershenson2002d,
	title = {A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition},
	year = {2002},
	school = {School of Cognitive and Computing Sciences, University of Sussex},
	type = {masters},
	abstract = {In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no {\textquoteleft}{\textquoteleft}best{\textquoteright}{\textquoteright} model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical aid, I note that there is no {\textquoteleft}{\textquoteleft}best{\textquoteright}{\textquoteright} approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on {\textquoteleft}{\textquoteleft}proper{\textquoteright}{\textquoteright} approaches for cognition: all approaches are a bit proper, but none will be {\textquoteleft}{\textquoteleft}proper enough{\textquoteright}{\textquoteright}. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition.},
	url = {http://www.cogs.susx.ac.uk/easy/Publications/Online/MSc2002/cg26.pdf},
	author = {Carlos Gershenson}
}
@conference {Gershenson2002a,
	title = {Complex Philosophy},
	booktitle = {Proceedings of the 1st Biennial Seminar on Philosophical, Methodological $\And$ Epistemological Implications of Complexity Theory},
	year = {2002},
	address = {La Habana, Cuba},
	abstract = {We present several philosophical ideas emerging from the studies of complex systems. We make a brief introduction to the basic concepts of complex systems, for then defining "abstraction levels". These are useful for representing regularities in nature. We define absolute being (observer independent, infinite) and relative being (observer dependent, finite), and notice the differences between them. We draw issues on relative causality and absolute causality among abstraction levels. We also make reflections on determinism. We reject the search for any absolute truth (because of their infinity), and promote the idea that all comprehensible truths are relative, since they were created in finite contexts. This leads us to suggest to search the less-incompleteness of ideas and contexts instead of their truths.},
	url = {http://uk.arXiv.org/abs/nlin.AO/0109001},
	author = {Carlos Gershenson}
}
@unpublished {Gershenson2002ua,
	title = {Contextuality: A Philosophical Paradigm, with Applications to Philosophy of Cognitive Science},
	year = {2002},
	note = {POCS Essay, COGS, University of Sussex},
	abstract = {We develop on the idea that everything is related, inside, and therefore determined by a context. This stance, which at first might seem obvious, has several important consequences. This paper first presents ideas on Contextuality, for then applying them to problems in philosophy of cognitive science. Because of space limitations, for the second part we will assume that the reader is familiar with the literature of philosophy of cognitive science, but if this is not the case, it would not be a limitation for understanding the main ideas of this paper. We do not argue that Contextuality is a panaceic answer for explaining everything, but we do argue that everything is inside a context. And because this is always, we sometimes ignore it, but we believe that many problems are dissolved with a contextual approach, noticing things we ignore because of their obviousity. We first give a notion of context. We present the idea that errors are just incongruencies inside a context. We also present previous ideas of absolute being, relative being, and lessincompleteness. We state that all logics, and also truth judgements, are contextdependent, and we develop a {\textquoteleft}{\textquoteleft}Context-dependant Logic{\textquoteright}{\textquoteright}. We apply ideas of Contextuality to problems in semantics, the problem of {\textquoteleft}{\textquoteleft}where is the mind{\textquoteright}{\textquoteright}, and the study of consciousness.},
	url = {http://cogprints.org/2621/},
	author = {Carlos Gershenson}
}
@article {Gershenson2002b,
	title = {Philosophical Ideas on the Simulation of Social Behaviour},
	journal = {Journal of Artificial Societies and Social Simulation},
	volume = {5},
	number = {3},
	year = {2002},
	abstract = {In this study we consider some of the philosophical issues that should be taken into account when simulating social behaviour. Even though the ideas presented here are philosophical, they should be of interest more to researchers simulating social behaviour than to philosophers, since we try to note some problems that researchers might not put much attention to. We give notions of what could be considered a social behaviour, and mention the problems that arise if we attempt to give a sharp definition of social behaviour in a broad context. We also briefly give useful concepts and ideas of complex systems and abstraction levels (Gershenson, 2002a), since any society can be seen as a complex system. We discuss the problems that arise while modelling social behaviour, mentioning the synthetic method as a useful approach for contrasting social theories, because of the complexities of the phenomena they model. In addition, we note the importance of the study of social behaviour for the understanding of cognition. We hope that the ideas presented here motivate the interest and debate of researchers simulating social behaviour in order to pay attention to the problems mentioned in this work, and attempt to provide more suitable solutions to them than the ones proposed here.},
	url = {http://jasss.soc.surrey.ac.uk/5/3/8.html},
	author = {Carlos Gershenson}
}
@unpublished {Gershenson2002ub,
	title = {Where is the problem of {\textquoteleft}{\textquoteleft}Where is the mind?{\textquoteright}{\textquoteright}?},
	year = {2002},
	note = {POCS Essay, COGS, University of Sussex},
	abstract = {We propose that the discussions about {\textquoteleft}{\textquoteleft}where the mind is{\textquoteright}{\textquoteright} depend directly on the metaphysical preconception and definition of {\textquoteleft}{\textquoteleft}mind{\textquoteright}{\textquoteright}. If we see the mind from one perspective (individualist), it will be only in the brain, and if we see it from another (active externalist), it will be embedded in the body and extended into the world. The {\textquoteleft}{\textquoteleft}whereabouts{\textquoteright}{\textquoteright} of the mind depends on our <concept|definition>1 of mind. Therefore, we should not ask if the mind is somewhere, but if it is somehow.},
	url = {http://cogprints.org/2620/},
	author = {Carlos Gershenson}
}
@unpublished {Gershenson2001a,
	title = {Artificial Societies of Intelligent Agents},
	year = {2001},
	note = {Unpublished BEng Thesis},
	publisher = {Fundaci{\'o}n Arturo Rosenblueth},
	abstract = {In this thesis we present our work, where we developed artificial societies of intelligent agents, in order to understand and simulate adaptive behaviour and social processes. We obtain this in three parallel ways: First, we present a behaviours production system capable of reproducing a high number of properties of adaptive behaviour and of exhibiting emergent lower cognition. Second, we introduce a simple model for social action, obtaining emergent complex social processes from simple interactions of imitation and induction of behaviours in agents. And third, we present our approximation to a behaviours virtual laboratory, integrating our behaviours production system and our social action model in animats. In our behaviours virtual laboratory, the user can perform a wide variety of experiments, allowing him or her to test the properties of our behaviours production system and our social action model, and also to understand adaptive and social behaviour. It can be accessed and downloaded through the Internet. Before presenting our proposals, we make an introduction to artificial intelligence and behaviour-based systems, and also we give notions of complex systems and artificial societies. In the last chapter of the thesis, we present experiments carried out in our behaviours virtual laboratory showing the main properties of our behaviours production system, of our social action model, and of our behaviours virtual laboratory itself. Finally, we discuss about the understanding of adaptive behaviour as a path for understanding cognition and its evolution.},
	url = {http://cogprints.org/1477/},
	author = {Carlos Gershenson}
}
@conference {Gershenson2001b,
	title = {Comments to Neutrosophy},
	booktitle = {Proceedings of the First International Conference on Neutrosophy, Neutrosophic Logic, Set, Probability and Statistics},
	year = {2001},
	pages = {139{\textendash}146},
	publisher = {Xiquan},
	organization = {Xiquan},
	address = {University of New Mexico, Gallup, NM},
	abstract = {Any system based on axioms is incomplete because the axioms cannot be proven from the system, just believed. But one system can be less-incomplete than other. Neutrosophy is less-incomplete than many other systems because it contains them. But this does not mean that it is finished, and it can always be improved. The comments presented here are an attempt to make Neutrosophy even less-incomplete. I argue that less-incomplete ideas are more useful, since we cannot perceive truth or falsity or indeterminacy independently of a context, and are therefore relative. Absolute being and relative being are defined. Also the "silly theorem problem" is posed, and its partial solution described. The issues arising from the incompleteness of our contexts are presented. We also note the relativity and dependance of logic to a context. We propose "metacontextuality" as a paradigm for containing as many contexts as we can, in order to be less-incomplete and discuss some possible consequences.},
	url = {http://uk.arxiv.org/abs/math.GM/0111237},
	author = {Carlos Gershenson},
	editor = {Florentin Smarandache}
}
@conference {Gershenson1999,
	title = {Modelling Emotions with Multidimensional Logic},
	booktitle = {Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society {(NAFIPS} {\textquoteright}99)},
	year = {1999},
	pages = {42{\textendash}46},
	publisher = {IEEE Press},
	organization = {IEEE Press},
	address = {New York City, NY},
	abstract = {One of the objectives of Artificial Intelligence has been the modelling of "human" characteristics, such as emotions, behaviour, conscience, etc. But in such characteristics we might find certain degree of contradiction. Previous work on modelling emotions and its problems are reviewed. A model for emotions is proposed using multidimensional logic, which handles the degree of contradiction that emotions might have. The model is oriented to simulate emotions in artificial societies. The proposed solution is also generalized for actions which might overcome contradiction (conflictive goals in agents, for example).},
	url = {http://tinyurl.com/yek3ms},
	author = {Carlos Gershenson}
}
@conference {Gershenson1998b,
	title = {Control de Tr{\'a}fico con Agentes: {CRASH}},
	booktitle = {Memorias {XI} Congreso Nacional {ANIEI}},
	year = {1998},
	address = {Xalapa, M{\'e}xico},
	abstract = {El simulador CRASH (Car and Road Automated Simulation in Hyperways) usa programaci{\'o}n orientada a agentes para modelar el tr{\'a}fico de una ciudad sin necesidad de sem{\'a}foros, tratando de demorar los veh\'{\i}culos el menor tiempo posible (y sin que se impacten). Esto se hace por medio de agentes en cada autom{\'o}vil y en cada cruce, y un control central. Se hace una breve introducci{\'o}n al modelo de programaci{\'o}n orientada a agentes, para despu{\'e}s explicar el modelo del simulador. Se describen las clases usadas en la implementaci{\'o}n, sus propiedades y sus relaciones, mostrando el diagrama de las clases. Finalmente, se exponen las conclusiones que se llegaron con las simulaciones.},
	url = {http://tinyurl.com/ybgwk8},
	author = {Carlos Gershenson}
}
@conference {Gershenson1998a,
	title = {L{\'o}gica Multidimensional: Un Modelo de L{\'o}gica Paraconsistente},
	booktitle = {Memorias {XI} Congreso Nacional {ANIEI}},
	year = {1998},
	pages = {132{\textendash}141},
	address = {Xalapa, M{\'e}xico},
	abstract = {La l{\'o}gica multidimensional es un nuevo sistema de l{\'o}gica propuesto para modelar l{\'o}gica paraconsistente. Una breve definici{\'o}n de l{\'o}gica paraconsistente y ejemplos de cuando es usada son dados. Se definen los principios y propiedades de la l{\'o}gica multidimensional, tales como las variables l{\'o}gicas multidimensionales. Los operadores l{\'o}gicos Y, O, NO, SI... ENTONCES y SI Y S{\'O}LO SI son definidos y explicados para la l{\'o}gica multidimensional. Adem{\'a}s, se definen equivalencia, grado de contradicci{\'o}n, y la proyecci{\'o}n de la l{\'o}gica multidimensional en la difusa. Esto incluye un peque{\~n}o programa que},
	url = {http://tinyurl.com/y9hb4e},
	author = {Carlos Gershenson}
}
@conference {Gershenson1997b,
	title = {Aplicaciones de la Topolog{\'\i}a},
	booktitle = {Memorias X Congreso Nacional {ANIEI}},
	year = {1997},
	address = {Monterrey, M{\'e}xico},
	abstract = {En el presente trabajo se abordan algunas aplicaciones de la Topolog\'{\i}a en la Computaci{\'o}n, como el Juego de la Vida. Se tratan de ampliar los conocimientos actuales sobre estas aplicaciones y sus representaciones gr{\'a}ficas. Se apoya la exposici{\'o}n con un simulador de tiempo c\'{\i}clico. Tambi{\'e}n se hace una propuesta para definir el Universo como un tiempo c\'{\i}clico.},
	url = {http://tinyurl.com/ym5vbz},
	author = {Carlos Gershenson}
}
@conference {Gershenson1997a,
	title = {El Juego de la Vida En 3D},
	booktitle = {Memorias X Congreso Nacional {ANIEI}},
	year = {1997},
	address = {Monterrey, M{\'e}xico},
	abstract = {Primero se introduce al lector con un poco de la historia del Juego de la Vida. Despu{\'e}s se explican sus consecuencias en dos dimensiones, y por {\'u}ltimo se discuten sus propiedades al llevar el Juego de la Vida a una tercera dimensi{\'o}n, y se muestran algunos ejemplos.},
	url = {http://tinyurl.com/y9j5ac},
	author = {Carlos Gershenson}
}
